Treffer: Analysis of the managing educational and research activities model based on the use of a hybrid neural network

Introduction. One of the central tasks of education is the development of students' abilities for research activities,which is a key tool for gaining a subjective understanding of the surrounding reality, the formation of critical thinking,and a scientific worldview. The solution to this problem in the context of large-scale digitalization of the educationalsphere can be achieved through the use of automated learning platforms with an intelligent component. Thepurpose of this study is to develop the technological foundations for the functioning of a neural network for modelinga personalized educational process in the context of using an intelligent learning system.Materials and methods. The key idea of the study is the possibility of intelligent management of researchactivities through the use of neural network functionality, which ensures adaptability and correction of the processof mastering the material depending on the learning style of the student, the level of training, and the degree ofdevelopment of independent work skills.Results. The structure of the generalized hybrid neural network is characterized, as a result of the functioningof which personalized parameters of the research potential of students are formed. The structure of the matrix ofparameters intended for the input layers of the neural network is described. A procedure for forming clusters of inputparameters of the generalized neural network is proposed. A series of computational experiments is performed, andan interpretation of the obtained results is given.Conclusion. The study makes a certain contribution to the development of technology for organizing researchactivities of students using intelligent control. It is aimed at identifying the potential of neural networks for solvingproblems of modeling individual educational trajectories and monitoring educational process indicators.